Developing and managing petroleum resources often entails committing large economic investments over many years with an expectation of receiving correspondingly large financial returns. Whether a petroleum reservoir yields profit or loss depends largely upon the strategies and tactics implemented for reservoir development and management. Reservoir development planning involves devising and/or selecting strong strategies and tactics that will yield favorable economic results over the long term.
Reservoir development planning may include making decisions regarding well trajectory, size, timing, and location of production platforms as well as subsequent expansions and connections, for example. Key decisions can involve the trajectory, number, location, allocation to platforms, and timing of wells to be drilled and completed in each field. The planners must also make key decisions concerning drilling and completion properties, such as the number, size, and setting depths of casing strings, sizes of drill pipe, drilling mud densities, flow rates, and required capabilities of surface equipment such as mud pumps. Any one decision or action may have system-wide implications, for example, propagating positive or negative impact across a petroleum operation or a reservoir. Thus, oil and gas well drilling should be a near-flawless operation wherein one or more subsurface targets are penetrated in a near-precise location and with an optimal wellbore orientation while suffering a minimal number of adverse drilling events such as lost circulation, stuck pipe, collisions with other wellbores, etc. In view of the aforementioned aspects of reservoir development planning, which are only a representative few of the many decisions facing a manager of petroleum resources, one can appreciate the value and impact of planning.
Computer-based modeling holds significant potential for reservoir development planning, particularly when combined with advanced mathematical techniques. Computer-based planning tools support making good decisions. One type of planning tool includes methodology for identifying an optimal solution to a set of decisions based on processing various information inputs. For example, an exemplary optimization model may work towards finding solutions that yield the best outcome from known possibilities with a defined set of constraints. Accordingly, a field development plan may achieve great economic benefit via properly applying optimization models for design of wells and for making decisions about the drilling and completion operations that create the wells.
The terms “optimal,” “optimizing,” “optimize,” “optimality,” “optimization” (as well as derivatives and other forms of those terms and linguistically related words and phrases), as used herein, are not intended to be limiting in the sense of requiring the present invention to find the best solution or to make the best decision. Although a mathematically optimal solution may in fact arrive at the best of all mathematically available possibilities, real-world embodiments of optimization routines, methods, models, and processes may work towards such a goal without ever actually achieving perfection. Accordingly, one of ordinary skill in the art having benefit of the present disclosure will appreciate that these terms, in the context of the scope of the present invention, are more general. The terms can describe working towards a solution which may be the best available solution, a preferred solution, or a solution that offers a specific benefit within a range of constraints; or continually improving; or refining; or searching for a high point or a maximum for an objective; or processing to reduce a penalty function; etc.
In certain exemplary embodiments, an optimization model can be an algebraic system of functions and equations comprising (1) decision variables of either continuous or integer variety which may be limited to specific domain ranges, (2) constraint equations, which are based on input data (parameters) and the decision variables, that restrict activity of the variables within a specified set of conditions that define feasibility of the optimization problem being addressed, and/or (3) an objective function based on input data (parameters) and the decision variables being optimized, either by maximizing the objective function or minimizing the objective function. In some variations, optimization models may include differential, black-box, and other non-algebraic functions or equations.
Although pivotal in the development plan of oil and gas fields, well trajectory planning has been an exercise of geometry. In conventional reservoir development planning technologies, the resulting well path is an input to the process of determining a well development plan. Frequently, well trajectory planning involves only the process of finding a solution that intersects the target(s) while avoiding other wells, with little or no attempt to optimize anything about the trajectory. The process begins with a well path that is based on a similar geometry from some nearby wells or is composed of interpolating segments joining surface locations and a set of pre-specified targets. This trajectory is input into the plan to drill the well while taking into account some geologic, mechanical and hydraulic constraints. This process may be iterative such that revisions to the trajectory are made in search of a feasible, lower risk, or lower cost plan. However, these revisions to the trajectory have been manual.
The conventional practice for determining a well trajectory is at best a manual process and can be time consuming. Additionally, the finally determined well trajectory may suffer shortcomings, including, but not limited to, lack of conformance to geologic, mechanical, and hydraulic constraints, not providing the best mechanical or economic well trajectory, and having limited capabilities for incorporating drilling environment uncertainty. Thus, the calculated well trajectory may miss an alternate well trajectory that produces a better overall objective, such as minimizing cost or maximizing probability of success.
In view of the foregoing discussion, need is apparent in the art for an improved tool that can aid reservoir development planning and/or that can provide decision support in connection with drilling and completion operations. A need further exists for a tool that can systematically address well trajectory within a model used to produce plans or decision support. A need further exists for a tool that can take into account the geologic, mechanical, and hydraulic constraints when determining the well trajectory. A need further exists for a tool that systematically addresses drilling environment uncertainty within a model used to produce well trajectory, reservoir development plans, and/or decision support. A need further exists for a tool that can integrate well trajectory planning and well development planning processes such that a well path, drilling program, and development plan are generated simultaneously or in concert with one another. The foregoing discussion of need in the art is intended to be representative rather than exhaustive. A technology addressing one or more such needs, or some other related shortcoming in the field, would benefit drilling and reservoir development planning, for example, providing decisions or plans for developing a reservoir more effectively and more profitably.